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Research Article | Open Access |

Big Data Processing for Full-Text Search and Visualization with Elasticsearch

Author 1: Aleksei Voit Author 2: Aleksei Stankus Author 3: Shamil Magomedov Author 4: Irina Ivanova
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 8, No. 12 · Published 2017 · Cited by 21

DOI: 10.14569/IJACSA.2017.081211

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Abstract

In this paper, the task of using Big Data to identify specific individuals on the indirect grounds of their interaction with information resources is considered. Possible sources of Big Data and problems related to its processing are analyzed. Existing means of data clustering are considered. Available software for full-text search and data visualization is analyzed, and a system based on Elasticsearch engine and MapReduce model is proposed for the solution of user verification problem.

Keywords

Big Data processing verification elasticsearch MapReduce data clustering

How to Cite this Article

Voit, A., Stankus, A., Magomedov, S., & Ivanova, I. (2017). Big Data Processing for Full-Text Search and Visualization with Elasticsearch. International Journal of Advanced Computer Science and Applications, 8(12). https://doi.org/10.14569/IJACSA.2017.081211

Voit, Aleksei, et al.. "Big Data Processing for Full-Text Search and Visualization with Elasticsearch." International Journal of Advanced Computer Science and Applications, vol. 8, no. 12, 2017, https://doi.org/10.14569/IJACSA.2017.081211.

@article{Voit2017,
  title     = {Big Data Processing for Full-Text Search and Visualization with Elasticsearch},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {12},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {Aleksei Voit and Aleksei Stankus and Shamil Magomedov and Irina Ivanova},
  doi       = {10.14569/IJACSA.2017.081211},
  url       = {https://doi.org/10.14569/IJACSA.2017.081211}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

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Call for Papers - Important Dates

Volume 17 No. 11, November 2026
Paper Submission Due October 25, 2026
Review Notification November 15, 2026
Publication Date November 30, 2026
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